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elevanaltd

debate-hall-mcp

by elevanaltd

resolve_question

Resolve a question by running a structured multi-perspective debate and returning a verified decision record, ready for immediate use.

Instructions

Resolve a question through structured debate and return decision record.

High-level Layer 3 API that combines run_debate + extract_decision_record into a single operation. Agents call this for quick, verified decisions.

Process:

  1. Generate thread_id if not provided (YYYY-MM-DD-topic-slug format)

  2. Run full Wind/Wall/Door debate via run_debate

  3. Extract DecisionRecord from closed debate

  4. Return verified decision ready for use

Args: topic: The question or topic to resolve tier: Tier configuration name (default: "standard") thread_id: Optional custom thread ID (auto-generated if None)

Returns: Dictionary with DecisionRecord fields plus debate metadata: - All DecisionRecord fields (identity, outcome, rationale, validation, provenance) - debate_result: The raw run_debate result for reference

Raises: RuntimeError: If debate fails or cannot be closed ValueError: If tier configuration is invalid

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tierNostandard
topicYes
thread_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full behavioral burden. It discloses the process (thread generation, debate run, decision extraction), the return payload, and the possible RuntimeError/ValueError outcomes. This is transparent enough, though it could mention persistence/side-effect details such as thread creation more explicitly.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with a purpose statement, numbered process, Args section, Returns section, and Raises section. It is detailed yet every sentence earns its place, with the primary purpose front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a multi-step tool with no annotations and an output schema, the description covers the full call flow: inputs, processing, return shape, and error conditions. Nothing an agent needs to call it correctly or understand its result is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, but the description compensates fully by explaining all three parameters: topic as the question, tier as a configuration name with a default, and thread_id as optional with auto-generation when None. This adds real meaning beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb ('Resolve a question') and resource ('structured debate... decision record'), and explicitly frames itself as a Layer 3 combination of run_debate + extract_decision_record. This clearly distinguishes it from sibling tools and leaves no ambiguity about what it does.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It says agents call this 'for quick, verified decisions' and explains that it wraps two lower-level tools into a single operation. This gives clear context for when to use it, though it does not explicitly state when not to use it or name alternative tools for raw debate access.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.